Maps application entry points and hot execution paths to streamline performance profiling and optimization.
The Performance Code Path Mapper is a specialized skill designed to accelerate performance engineering by identifying the most critical code paths and implementation files before a profiling session begins. By leveraging repository mapping and dependency analysis across languages like Rust, Go, Python, and Java, it pinpoints candidate files and symbols associated with specific performance scenarios. This evidence-backed approach ensures that subsequent profiling and debugging efforts are focused on the areas most likely to impact system responsiveness and resource efficiency.
Key Features
01Standardized output format for integration into performance workflows
02Evidence-backed ranking of the most relevant 10-15 candidate files
03Multi-language support for Rust, Java, JS/TS, Go, and Python
04Extraction of relevant call chains, imports, and symbol exports
05Automated discovery of entry points and handlers via repo-map and grep
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Use Cases
01Mapping complex execution flows in unfamiliar codebases to find potential bottlenecks
02Pre-profiling analysis to narrow down investigation areas for latency issues
03Identifying hot paths and critical symbols before performing flamegraph analysis
